Maternal psychosocial risk factors and child gestational epigenetic age in a South African birth cohort study.

Accelerated epigenetic aging relative to chronological age has been found to be associated with higher risk of mortality in adults. However, little is known about whether and how in utero exposures might shape child gestational epigenetic age (EA) at birth. We aimed to explore associations between maternal psychosocial risk factors and deviation in child gestational EA at birth (i.e., greater or lower EA relative to chronological age) in a South African birth cohort study-the Drakenstein Child Health Study. Maternal psychosocial risk factors included trauma/stressor exposure; posttraumatic stress disorder (PTSD); depression; psychological distress; and alcohol/tobacco use. Child gestational EA at birth was calculated using an epigenetic clock previously devised for neonates; and gestational EA deviation was calculated as the residuals of the linear model between EA and chronological gestational age. Bivariate linear regression was then used to explore unadjusted associations between maternal/child risk factors and child gestational EA residuals at birth. Thereafter, a multivariable regression method was used to determine adjusted associations. Data from 271 maternal-child dyads were included in the current analysis. In the multivariable regression model, maternal PTSD was significantly and negatively associated with child gestational EA residuals at birth (ß = -1.95; p = 0.018), controlling for study site, sex of the child, head circumference at birth, birthweight, mode of delivery, maternal estimated household income, body mass index (BMI) at enrolment, HIV status, anaemia, psychological distress, and prenatal tobacco or alcohol use. Given the novelty of this preliminary finding, and its potential translational relevance, further studies to delineate underlying biological pathways and to explore clinical implications of EA deviation are warranted.

Methylation of cysteinyl leukotriene receptor 1 genes associates with lung function in asthmatics exposed to traffic-related air pollution.

Air pollution is associated with early declines in lung function and increased levels of asthma-related cysteinyl leukotrienes (CysLT) but a biological pathway linking this rapid response has not been delineated. In this randomized controlled diesel exhaust (DE) challenge study of 16 adult asthmatics, increased exposure-attributable urinary leukotriene E4 (uLTE4, a biomarker of cysteinyl leukotriene production) was correlated (p = 0.04) with declines in forced expiratory volume in 1-second (FEV1) within 6 hours of exposure. Exposure-attributable uLTE4 increases were correlated (p = 0.02) with increased CysLT receptor 1 (CysLTR1) methylation in peripheral blood mononuclear cells which, in turn, was marginally correlated (p = 0.06) with decreased CysLTR1 expression. Decreased CysLTR1 expression was, in turn, correlated (p = 0.0007) with FEV1 declines. During the same time period, increased methylation of GPR17 (a negative regulator of CysLTR1) was observed after DE exposure (p = 0.02); this methylation increase was correlated (p = 0.001) with decreased CysLTR1 methylation which, in turn, was marginally correlated (p = 0.06) with increased CysLTR1 expression; increased CysLTR1 expression was correlated (p = 0.0007) with FEV1 increases. Collectively, these data delineate a potential mechanistic pathway linking increased DE exposure-attributable CysLT levels to lung function declines through changes in CysLTR1-related methylation and gene expression.

Parenting Interacts With Plasticity Genes in Predicting Behavioral Outcomes in Preschoolers.

BACKGROUND: Public health and pediatric nurses typically focus on supporting parenting to reduce the likelihood of children's behavioral problems. Studies have identified interactions between early exposures to stress in caregiving and child genotype in predicting children's behavioral problems, such that certain genotypes connote greater differential susceptibility or plasticity to environmental stressors. We sought to uncover the interaction between observational measures of parent-child relationship quality and genotype in predicting early-onset behavioral problems in 24-month-olds, using prospective methods. METHODS: We conducted a secondary analysis of data collected on a subsample of 176 women and their infants enrolled during pregnancy in the ongoing Alberta Pregnancy Outcomes and Nutrition (APrON) cohort study. Inclusion criteria required mothers to be ≥18 years of age, English speaking and ≤22 weeks gestational age at enrollment. Genetic data were obtained from blood leukocytes and buccal epithelial cell samples, collected from infants at three months of age. For each child, the presence of plasticity alleles was determined for BDNF, CNR1, DRD2/ANKK1, DRD4, DAT1, 5-HTTLPR, and MAOA and an overall index was calculated to summarize the number of plasticity alleles present. Observational assessments of parent-child relationship quality (sensitivity, controlling, and unresponsiveness) were conducted at six months of age. Children's internalizing (e.g., emotionally reactive, anxious/depressed, somatic complaint, withdrawn) and externalizing (e.g., aggression, inattention) behaviors were assessed at 24 months of age. After extracting genetic data, a maximum likelihood method for regressions was employed with Akaike Information Criterion (AIC) for model selection. RESULTS: When parents were less responsive and children possessed more plasticity alleles, children were more likely to be emotionally reactive, anxious/depressed, report somatic complaints, and withdrawn, while when parents were less responsive and children possessed fewer plasticity alleles, children were less likely to display these internalizing behaviors, in a differentially susceptible manner. Furthermore, when parents were more responsive, and children possessed more plasticity alleles, children were less likely to display internalizing behaviors (P = 0.034). Similarly, children who possessed either the CNR1-A plasticity allele (P = 0.010) or DAT1 9-repeat plasticity allele (P = 0.036) and experienced more/less parental control displayed more/fewer externalizing problems, respectively, in a differentially susceptible manner. CONCLUSIONS: The plasticity index score interacted with parental unresponsiveness in predicting anxiety and depressive behavioral problems in children, while individual genetic variants interacted with parental controlling behavior in predicting aggression and inattention in children, suggestive of differential susceptibility to caregiving. Especially in the context of nursing interventions designed to support childrearing and children's development, nurses need to be aware of the interactions between child genotype and parenting in understanding how well interventions will work in promoting optimal child behavior.

Systematic evaluation of DNA methylation age estimation with common preprocessing methods and the Infinium MethylationEPIC BeadChip array.

BACKGROUND: The capacity of technologies measuring DNA methylation (DNAm) is rapidly evolving, as are the options for applicable bioinformatics methods. The most commonly used DNAm microarray, the Illumina Infinium HumanMethylation450 (450K array), has recently been replaced by the Illumina Infinium HumanMethylationEPIC (EPIC array), nearly doubling the number of targeted CpG sites. Given that a subset of 450K CpG sites is absent on the EPIC array and that several tools for both data normalization and analyses were developed on the 450K array, it is important to assess their utility when applied to EPIC array data. One of the most commonly used 450K tools is the pan-tissue epigenetic clock, a multivariate predictor of biological age based on DNAm at 353 CpG sites. Of these CpGs, 19 are missing from the EPIC array, thus raising the question of whether EPIC data can be used to accurately estimate DNAm age. We also investigated a 71-CpG epigenetic age predictor, referred to as the Hannum method, which lacks 6 probes on the EPIC array. To evaluate these epigenetic clocks in EPIC data properly, a prior assessment of the effects of data preprocessing methods on DNAm age is also required. METHODS: DNAm was quantified, on both the 450K and EPIC platforms, from human primary monocytes derived from 172 individuals. We calculated DNAm age from raw, and three different preprocessed data forms to assess the effects of different processing methods on the DNAm age estimate. Using an additional cohort, we also investigated DNAm age of peripheral blood mononuclear cells, bronchoalveolar lavage, and bronchial brushing samples using the EPIC array. RESULTS: Using monocyte-derived data from subjects on both the 450K and EPIC, we found that DNAm age was highly correlated across both raw and preprocessing methods (r > 0.91). Thus, the correlation between chronological age and the DNAm age estimate is largely unaffected by platform differences and normalization methods. However, we found that the choice of normalization method and measurement platform can lead to a systematic offset in the age estimate which in turn leads to an increase in the median error. Comparing the 450K and EPIC DNAm age estimates, we observed that the median absolute difference was 1.44-3.10 years across preprocessing methods. CONCLUSIONS: Here, we have provided evidence that the epigenetic clock is resistant to the lack of 19 CpG sites missing from the EPIC array as well as highlighted the importance of considering the technical variance of the epigenetic when interpreting group differences below the reported error. Furthermore, our study highlights the utility of epigenetic age acceleration measure, the residuals from a linear regression of DNAm age on chronological age, as the resulting values are robust with respect to normalization methods and measurement platforms.

DNA methylation as a predictor of fetal alcohol spectrum disorder.

Background: Fetal alcohol spectrum disorder (FASD) is a developmental disorder that manifests through a range of cognitive, adaptive, physiological, and neurobiological deficits resulting from prenatal alcohol exposure. Although the North American prevalence is currently estimated at 2-5%, FASD has proven difficult to identify in the absence of the overt physical features characteristic of fetal alcohol syndrome. As interventions may have the greatest impact at an early age, accurate biomarkers are needed to identify children at risk for FASD. Building on our previous work identifying distinct DNA methylation patterns in children and adolescents with FASD, we have attempted to validate these associations in a different clinical cohort and to use our DNA methylation signature to develop a possible epigenetic predictor of FASD. Methods: Genome-wide DNA methylation patterns were analyzed using the Illumina HumanMethylation450 array in the buccal epithelial cells of a cohort of 48 individuals aged 3.5-18 (24 FASD cases, 24 controls). The DNA methylation predictor of FASD was built using a stochastic gradient boosting model on our previously published dataset FASD cases and controls (GSE80261). The predictor was tested on the current dataset and an independent dataset of 48 autism spectrum disorder cases and 48 controls (GSE50759). Results: We validated findings from our previous study that identified a DNA methylation signature of FASD, replicating the altered DNA methylation levels of 161/648 CpGs in this independent cohort, which may represent a robust signature of FASD in the epigenome. We also generated a predictive model of FASD using machine learning in a subset of our previously published cohort of 179 samples (83 FASD cases, 96 controls), which was tested in this novel cohort of 48 samples and resulted in a moderately accurate predictor of FASD status. Upon testing the algorithm in an independent cohort of individuals with autism spectrum disorder, we did not detect any bias towards autism, sex, age, or ethnicity. Conclusion: These findings further support the association of FASD with distinct DNA methylation patterns, while providing a possible entry point towards the development of epigenetic biomarkers of FASD.

Choice of surrogate tissue influences neonatal EWAS findings.

BACKGROUND: Epigenomes are tissue specific and thus the choice of surrogate tissue can play a critical role in interpreting neonatal epigenome-wide association studies (EWAS) and in their extrapolation to target tissue. To develop a better understanding of the link between tissue specificity and neonatal EWAS, and the contributions of genotype and prenatal factors, we compared genome-wide DNA methylation of cord tissue and cord blood, two of the most accessible surrogate tissues at birth. METHODS: In 295 neonates, DNA methylation was profiled using Infinium HumanMethylation450 beadchip arrays. Sites of inter-individual variability in DNA methylation were mapped and compared across the two surrogate tissues at birth, i.e., cord tissue and cord blood. To ascertain the similarity to target tissues, DNA methylation profiles of surrogate tissues were compared to 25 primary tissues/cell types mapped under the Epigenome Roadmap project. Tissue-specific influences of genotype on the variable CpGs were also analyzed. Finally, to interrogate the impact of the in utero environment, EWAS on 45 prenatal factors were performed and compared across the surrogate tissues. RESULTS: Neonatal EWAS results were tissue specific. In comparison to cord blood, cord tissue showed higher inter-individual variability in the epigenome, with a lower proportion of CpGs influenced by genotype. Both neonatal tissues were good surrogates for target tissues of mesodermal origin. They also showed distinct phenotypic associations, with effect sizes of the overlapping CpGs being in the same order of magnitude. CONCLUSIONS: The inter-relationship between genetics, prenatal factors and epigenetics is tissue specific, and requires careful consideration in designing and interpreting future neonatal EWAS. TRIAL REGISTRATION: This birth cohort is a prospective observational study, designed to study the developmental origins of health and disease, and was retrospectively registered on 1 July 2010 under the identifier NCT01174875 .

Maternal blood contamination of collected cord blood can be identified using DNA methylation at three CpGs.

BACKGROUND: Cord blood is a commonly used tissue in environmental, genetic, and epigenetic population studies due to its ready availability and potential to inform on a sensitive period of human development. However, the introduction of maternal blood during labor or cross-contamination during sample collection may complicate downstream analyses. After discovering maternal contamination of cord blood in a cohort study of 150 neonates using Illumina 450K DNA methylation (DNAm) data, we used a combination of linear regression and random forest machine learning to create a DNAm-based screening method. We identified a panel of DNAm sites that could discriminate between contaminated and non-contaminated samples, then designed pyrosequencing assays to pre-screen DNA prior to being assayed on an array. RESULTS: Maternal contamination of cord blood was initially identified by unusual X chromosome DNA methylation patterns in 17 males. We utilized our DNAm panel to detect contaminated male samples and a proportional amount of female samples in the same cohort. We validated our DNAm screening method on an additional 189 sample cohort using both pyrosequencing and DNAm arrays, as well as 9 publically available cord blood 450K data sets. The rate of contamination varied from 0 to 10% within these studies, likely related to collection specific methods. CONCLUSIONS: Maternal blood can contaminate cord blood during sample collection at appreciable levels across multiple studies. We have identified a panel of markers that can be used to identify this contamination, either post hoc after DNAm arrays have been completed, or in advance using a targeted technique like pyrosequencing.

DNA methylation signatures of chronic alcohol dependence in purified CD3+ T-cells of patients undergoing alcohol treatment.

Several studies have shown an association of alcohol dependence with DNA methylation (DNAm), suggesting that environmentally-induced changes on epigenomic variation may play an important role in alcohol dependence. In the present study, we analysed genome-wide DNAm profiles of purified CD3+ T-cells from pre- and post-treatment alcohol dependent patients, as well as closely matched healthy controls. We identified 59 differentially methylated CpG sites comparing patients prior to treatment with healthy controls and were able to confirm 8 of those sites in additional analyses for differentially methylated regions. Comparing patients before and after a 3-week alcohol treatment program we revealed another unique set of 48 differentially methylated CpG sites. Additionally, we found that the mean global DNAm was significantly lower in patients prior to treatment compared to controls, but reverted back to levels similar to controls after treatment. We validated top-ranked hits derived from the epigenome-wide analysis by pyrosequencing and further replicated two of them in an independent cohort and confirmed differential DNAm of HECW2 and SRPK3 in whole blood. This study is the first to show widespread DNAm variation in a disease-relevant blood cell type and implicates HECW2 and SRPK3 DNAm as promising blood-based candidates to follow up in future studies.

Social and physical environments early in development predict DNA methylation of inflammatory genes in young adulthood.

Chronic inflammation contributes to a wide range of human diseases, and environments in infancy and childhood are important determinants of inflammatory phenotypes. The underlying biological mechanisms connecting early environments with the regulation of inflammation in adulthood are not known, but epigenetic processes are plausible candidates. We tested the hypothesis that patterns of DNA methylation (DNAm) in inflammatory genes in young adulthood would be predicted by early life nutritional, microbial, and psychosocial exposures previously associated with levels of inflammation. Data come from a population-based longitudinal birth cohort study in metropolitan Cebu, the Philippines, and DNAm was characterized in whole blood samples from 494 participants (age 20-22 y). Analyses focused on probes in 114 target genes involved in the regulation of inflammation, and we identified 10 sites across nine genes where the level of DNAm was significantly predicted by the following variables: household socioeconomic status in childhood, extended absence of a parent in childhood, exposure to animal feces in infancy, birth in the dry season, or duration of exclusive breastfeeding. To evaluate the biological significance of these sites, we tested for associations with a panel of inflammatory biomarkers measured in plasma obtained at the same age as DNAm assessment. Three sites predicted elevated inflammation, and one site predicted lower inflammation, consistent with the interpretation that levels of DNAm at these sites are functionally relevant. This pattern of results points toward DNAm as a potentially important biological mechanism through which developmental environments shape inflammatory phenotypes across the life course.

Differential DNA methylation and lymphocyte proportions in a Costa Rican high longevity region.

BACKGROUND: The Nicoya Peninsula in Costa Rica has one of the highest old-age life expectancies in the world, but the underlying biological mechanisms of this longevity are not well understood. As DNA methylation is hypothesized to be a component of biological aging, we focused on this malleable epigenetic mark to determine its association with current residence in Nicoya versus elsewhere in Costa Rica. Examining a population's unique DNA methylation pattern allows us to differentiate hallmarks of longevity from individual stochastic variation. These differences may be characteristic of a combination of social, biological, and environmental contexts. METHODS: In a cross-sectional subsample of the Costa Rican Longevity and Healthy Aging Study, we compared whole blood DNA methylation profiles of residents from Nicoya (n = 48) and non-Nicoya (other Costa Rican regions, n = 47) using the Infinium HumanMethylation450 microarray. RESULTS: We observed a number of differences that may be markers of delayed aging, such as bioinformatically derived differential CD8+ T cell proportions. Additionally, both site- and region-specific analyses revealed DNA methylation patterns unique to Nicoyans. We also observed lower overall variability in DNA methylation in the Nicoyan population, another hallmark of younger biological age. CONCLUSIONS: Nicoyans represent an interesting group of individuals who may possess unique immune cell proportions as well as distinct differences in their epigenome, at the level of DNA methylation.

Developmental pathways to adiposity begin before birth and are influenced by genotype, prenatal environment and epigenome.

BACKGROUND: Obesity is an escalating health problem worldwide, and hence the causes underlying its development are of primary importance to public health. There is growing evidence that suboptimal intrauterine environment can perturb the metabolic programing of the growing fetus, thereby increasing the risk of developing obesity in later life. However, the link between early exposures in the womb, genetic susceptibility, and perturbed epigenome on metabolic health is not well understood. In this study, we shed more light on this aspect by performing a comprehensive analysis on the effects of variation in prenatal environment, neonatal methylome, and genotype on birth weight and adiposity in early childhood. METHODS: In a prospective mother-offspring cohort (N = 987), we interrogated the effects of 30 variables that influence the prenatal environment, umbilical cord DNA methylation, and genotype on offspring weight and adiposity, over the period from birth to 48 months. This is an interim analysis on an ongoing cohort study. RESULTS: Eleven of 30 prenatal environments, including maternal adiposity, smoking, blood glucose and plasma unsaturated fatty acid levels, were associated with birth weight. Polygenic risk scores derived from genetic association studies on adult adiposity were also associated with birth weight and child adiposity, indicating an overlap between the genetic pathways influencing metabolic health in early and later life. Neonatal methylation markers from seven gene loci (ANK3, CDKN2B, CACNA1G, IGDCC4, P4HA3, ZNF423 and MIRLET7BHG) were significantly associated with birth weight, with a subset of these in genes previously implicated in metabolic pathways in humans and in animal models. Methylation levels at three of seven birth weight-linked loci showed significant association with prenatal environment, but none were affected by polygenic risk score. Six of these birth weight-linked loci continued to show a longitudinal association with offspring size and/or adiposity in early childhood. CONCLUSIONS: This study provides further evidence that developmental pathways to adiposity begin before birth and are influenced by environmental, genetic and epigenetic factors. These pathways can have a lasting effect on offspring size, adiposity and future metabolic outcomes, and offer new opportunities for risk stratification and prevention of obesity. CLINICAL TRIAL REGISTRATION: This birth cohort is a prospective observational study, designed to study the developmental origins of health and disease, and was retrospectively registered on 1 July 2010 under the identifier NCT01174875 .

funtooNorm: an R package for normalization of DNA methylation data when there are multiple cell or tissue types.

MOTIVATION: DNA methylation patterns are well known to vary substantially across cell types or tissues. Hence, existing normalization methods may not be optimal if they do not take this into account. We therefore present a new R package for normalization of data from the Illumina Infinium Human Methylation450 BeadChip (Illumina 450 K) built on the concepts in the recently published funNorm method, and introducing cell-type or tissue-type flexibility. RESULTS: funtooNorm is relevant for data sets containing samples from two or more cell or tissue types. A visual display of cross-validated errors informs the choice of the optimal number of components in the normalization. Benefits of cell (tissue)-specific normalization are demonstrated in three data sets. Improvement can be substantial; it is strikingly better on chromosome X, where methylation patterns have unique inter-tissue variability. AVAILABILITY AND IMPLEMENTATION: An R package is available at https://github.com/GreenwoodLab/funtooNorm, and has been submitted to Bioconductor at http://bioconductor.org.

Bacterial infection remodels the DNA methylation landscape of human dendritic cells.

DNA methylation is an epigenetic mark thought to be robust to environmental perturbations on a short time scale. Here, we challenge that view by demonstrating that the infection of human dendritic cells (DCs) with a live pathogenic bacteria is associated with rapid and active demethylation at thousands of loci, independent of cell division. We performed an integrated analysis of data on genome-wide DNA methylation, histone mark patterns, chromatin accessibility, and gene expression, before and after infection. We found that infection-induced demethylation rarely occurs at promoter regions and instead localizes to distal enhancer elements, including those that regulate the activation of key immune transcription factors. Active demethylation is associated with extensive epigenetic remodeling, including the gain of histone activation marks and increased chromatin accessibility, and is strongly predictive of changes in the expression levels of nearby genes. Collectively, our observations show that active, rapid changes in DNA methylation in enhancers play a previously unappreciated role in regulating the transcriptional response to infection, even in nonproliferating cells.

HIF3A association with adiposity: the story begins before birth.

AIM: Determine if the association of HIF3A DNA methylation with weight and adiposity is detectable early in life. MATERIAL & METHODS: We determined HIF3A genotype and DNA methylation patterns (on hybridization arrays) in DNA extracted from umbilical cords of 991 infants. Methylation levels at three CpGs in the HIF3A first intron were related to neonatal and infant anthropometry and to genotype at nearby polymorphic sites. RESULTS & CONCLUSION: Higher methylation levels at three previously described HIF3A CpGs were associated with greater infant weight and adiposity. The effect sizes were slightly smaller than those reported for adult BMI. There was also an interaction within cis-genotype. The association between higher DNA methylation at HIF3A and increased adiposity is present in neonates. In this study, no particular prenatal factor strongly influenced HIF3A hypermethylation. Our data nonetheless suggest shared prenatal influences on HIF3A methylation and adiposity.